A Systematic Evaluation of Generative Models on Tabular Transportation Data

Bishop, C.M., Nasrabadi, N.M.: Pattern recognition and machine learning, vol. 4. Springer (2006)

2006

Earlier work this paper cites.

Kingma, D.P., Welling, M.: Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)

Original

2013

Earlier work this paper cites.

Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. Advances in neural information processing systems 27

2014

Earlier work this paper cites.

Patki, N., Wedge, R., Veeramachaneni, K.: The synthetic data vault. In: 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA). pp. 399–410 (2016). https://doi.org/10.1109/DSAA.2016.49

2016

Earlier work this paper cites.

Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein generative adversarial networks. In: International conference on machine learning. pp. 214–223. PMLR (2017)

2017

Earlier work this paper cites.

Correa, D.: Exploring the taxi and uber demands in new york city: An empirical analysis and spatial modeling. Available at SSRN 4229042 (2017)

2017

Earlier work this paper cites.

Shokri, R., Stronati, M., Song, C., Shmatikov, V.: Membership inference attacks against machine learning models. In: 2017 IEEE Symposium on Security and Privacy (SP). pp. 3–18 (2017). https://doi.org/10.1109/SP.2017.41

2017

Earlier work this paper cites.

Hilprecht, B., Härterich, M., Bernau, D.: Reconstruction and membership inference attacks against generative models. arXiv preprint arXiv:1906.03006 (2019)

Original

2019

Earlier work this paper cites.

Kynkäänniemi, T., Karras, T., Laine, S., Lehtinen, J., Aila, T.: Improved precision and recall metric for assessing generative models. Curran Associates Inc., Red Hook, NY, USA (2019)

2019

Earlier work this paper cites.

Xu, L., Skoularidou, M., Cuesta-Infante, A., Veeramachaneni, K.: Modeling tabular data using conditional gan. Advances in neural information processing systems 32

2019

Earlier work this paper cites.

Fan, J., Liu, T., Li, G., Chen, J., Shen, Y., Du, X.: Relational data synthesis using generative adversarial networks: A design space exploration. arXiv preprint arXiv:2008.12763 (2020)

Original

2020

Earlier work this paper cites.

Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Advances in neural information processing systems 33

2020

Cited alongside, same era.

Naeem, M.F., Oh, S.J., Uh, Y., Choi, Y., Yoo, J.: Reliable fidelity and diversity metrics for generative models. In: International Conference on Machine Learning. pp. 7176–7185. PMLR (2020)

2020

Cited alongside, same era.

Song, Y., Sohl-Dickstein, J., Kingma, D.P., Kumar, A., Ermon, S., Poole, B.: Score-based generative modeling through stochastic differential equations. arXiv preprint arXiv:2011.13456 (2020)

Original

2020

Cited alongside, same era.

Hoogeboom, E., Nielsen, D., Jaini, P., Forré, P., Welling, M.: Argmax flows and multinomial diffusion: Learning categorical distributions. Advances in Neural Information Processing Systems 34

2021

Cited alongside, same era.

Stadler, T., Oprisanu, B., Troncoso, C.: Synthetic data–anonymisation groundhog day. In: 31st USENIX Security Symposium (USENIX Security 22). pp. 1451–1468 (2022)

2022

Later among the works it cites.

Thompson, R., Knyazev, B., Ghalebi, E., Kim, J., Taylor, G.W.: On evaluation metrics for graph generative models. arXiv preprint arXiv:2201.09871 (2022)

Original

2022

Later among the works it cites.

Boudewijn, A.T.P., Ferraris, A.F., Panfilo, D., Cocca, V., Zinutti, S., De Schepper, K., Chauvenet, C.R.: Privacy measurements in tabular synthetic data: State of the art and future research directions. In: NeurIPS 2023 Workshop on Synthetic Data Generation with Generative AI (2023)

2023

Later among the works it cites.

Kotelnikov, A., Baranchuk, D., Rubachev, I., Babenko, A.: Tabddpm: Modelling tabular data with diffusion models. In: International Conference on Machine Learning. pp. 17564–17579. PMLR (2023)

2023

Later among the works it cites.